How to connect and process Webex data from Azure Databricks
Databricks is a cloud-based service that provides data processing capabilities through Apache Spark. When paired with the CData JDBC Driver, customers can use Databricks to perform data engineering and data science on live Webex data. This article explains how to host the CData JDBC Driver in Azure, as well as connect to and process live Webex data in Databricks.
With built-in optimized data processing, the CData JDBC driver offers unmatched performance for interacting with live Webex data. When you issue complex SQL queries to Webex, the driver pushes supported SQL operations, like filters and aggregations, directly to Webex and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations). Its built-in dynamic metadata querying allows you to work with and analyze Webex data using native data types.
Install the CData JDBC Driver in Azure
To work with live Webex data in Databricks, install the driver through Azure Data Lake Storage (ADLS). (Please note that the method of connecting through DBFS, which previous versions of this article described, has been deprecated, but has not published an end-of-life.)
- Upload the JDBC JAR file to a blob container of your choice (i.e. "jdbcjars" container of the "databrickslibraries" storage account).
- Fetch the Account Key from the storage account by expanding "Security + networking" and clicking on "Access Keys". Show and copy whichever of the two keys you wish to use.
- Get the JDBC JAR file's URL by navigating to Containers, opening the specific container storing the JAR, and selecting the entry for the JDBC JAR file. This should open the file's details, where there should be a convenient button to copy the URL button to clipboard. This value will look similar to the below, though the "blob" component may vary depending on storage account type:
https://databrickslibraries.blob.core.windows.net/jdbcjars/cdata.jdbc.salesforce.jar
- In the Configuration tab of your Databricks cluster, click on the Edit button and expand "Advanced options". From there, add the following Spark option (derived from the JAR URL's domain name) with your copied Account key as its value and click Confirm:
spark.hadoop.fs.azure.account.key.databrickslibraries.blob.core.windows.net
- In the Libraries tab of your Databricks cluster, click on "Install new", and select the ADLS option. Specify the ABFSS URL for the driver JAR (also derived from the JAR URL's domain name), and click Install. The ABFSS URL should resemble the below:
abfss://[email protected]/cdata.jdbc.salesforce.jar
Connect to Webex from Databricks
With the JAR file installed, we are ready to work with live Webex data in Databricks. Start by creating a new notebook in your workspace. Name the workbook, make sure Python is selected as the language (which should be by default), click on Connect and under General Compute select the cluster where you installed the JDBC driver (should be selected by default).
Configure the Connection to Webex
Connect to Webex by referencing the class for the JDBC Driver and constructing a connection string to use in the JDBC URL. Additionally, you will need to set the RTK property in the JDBC URL (unless you are using a Beta driver). You can view the licensing file included in the installation for information on how to set this property.
driver = "cdata.jdbc.api.APIDriver" url = "jdbc:api:RTK=5246...;Profile=C:\profiles\Webex.apip;Authscheme=OAuth;InitiateOAuth=GETANDREFRESH;OAuthClientId=your_client_id;OAuthClientSecret=your_client_secret;CallbackUrl=your_callback_url;ProfileSettings='Scope=your_scopes';"
Built-in Connection String Designer
For assistance in constructing the JDBC URL, use the connection string designer built into the Webex JDBC Driver. Either double-click the JAR file or execute the JAR file from the command-line.
java -jar cdata.jdbc.api.jar
Fill in the connection properties and copy the connection string to the clipboard.
To authenticate to Webex, and connect to your own data or to allow other users to connect to their data, you can use the OAuth standard.
Using OAuth Authentication
First, you will need to register an OAuth application with Webex. To do so, navigate to the Webex Developer Portal and create a new integration. Your OAuth application will be assigned a client id and a client secret.
After setting the following connection properties, you are ready to connect:
- AuthScheme: Set this to OAuth.
- InitiateOAuth: Set this to GETANDREFRESH. You can use InitiateOAuth to manage the process to obtain the OAuthAccessToken.
- OAuthClientId: Set this to the client_id that is specified in your app settings.
- OAuthClientSecret: Set this to the client_secret that is specified in your app settings.
- CallbackURL: Set this to the Redirect URI that is specified in your app settings.
- Scope: Set this in ProfileSettings to specify the OAuth scopes requested during authorization. Multiple scopes can be space-separated (e.g. ProfileSettings='Scope=spark:all spark:kms').
Example connection string:
Profile=C:\profiles\Webex.apip;Authscheme=OAuth;InitiateOAuth=GETANDREFRESH;OAuthClientId=your_client_id;OAuthClientSecret=your_client_secret;CallbackUrl=your_callback_url;ProfileSettings='Scope=your_scopes';
Load Webex Data
Once the connection is configured, you can load Webex data as a dataframe using the CData JDBC Driver and the connection information.
remote_table = spark.read.format ( "jdbc" ) \ .option ( "driver" , driver) \ .option ( "url" , url) \ .option ( "dbtable" , "AdminAuditEvents") \ .load ()
Display Webex Data
Check the loaded Webex data by calling the display function.
display (remote_table.select (""))
Analyze Webex Data in Azure Databricks
If you want to process data with Databricks SparkSQL, register the loaded data as a Temp View.
remote_table.createOrReplaceTempView ( "SAMPLE_VIEW" )
The SparkSQL below retrieves the Webex data for analysis.
result = spark.sql("SELECT , FROM SAMPLE_VIEW WHERE OrgId = 'org123'")
The data from Webex is only available in the target notebook. If you want to use it with other users, save it as a table.
remote_table.write.format ( "parquet" ) .saveAsTable ( "SAMPLE_TABLE" )
Download a free, 30-day trial of the CData API Driver for JDBC and start working with your live Webex data in Azure Databricks. Reach out to our Support Team if you have any questions.